otava list-groups
Lists all available test groups - high-level categories of tests.
otava list-tests [group name]
Lists all tests or the tests within a given group, if the group name is provided.
To list all available metrics defined for the test:
otava list-metrics <test>
[!TIP] See otava.yaml for the full example configuration.
$ otava list-metrics local.sample metric1 metric2
otava analyze <test>... otava analyze <group>...
This command prints interesting results of all runs of the test and a list of change-points. A change-point is a moment when a metric value starts to differ significantly from the values of the earlier runs and when the difference is persistent and statistically significant that it is unlikely to happen by chance. Otava calculates the probability (P-value) that the change point was caused by chance - the closer to zero, the more “sure” it is about the regression or performance improvement. The smaller is the actual magnitude of the change, the more data points are needed to confirm the change, therefore Otava may not notice the regression immediately after the first run that regressed. However, it will eventually identify the specific commit that caused the regression, as it analyzes the history of changes rather than just the HEAD of a branch.
The analyze command accepts multiple tests or test groups. The results are simply concatenated.
[!TIP] See otava.yaml for the full example configuration and local_samples.csv for the data.
$ otava analyze local.sample --since=2024-01-01
INFO: Computing change points for test sample.csv...
sample:
time metric1 metric2
------------------------- --------- ---------
2021-01-01 02:00:00 +0000 154023 10.43
2021-01-02 02:00:00 +0000 138455 10.23
2021-01-03 02:00:00 +0000 143112 10.29
2021-01-04 02:00:00 +0000 149190 10.91
2021-01-05 02:00:00 +0000 132098 10.34
2021-01-06 02:00:00 +0000 151344 10.69
·········
-12.9%
·········
2021-01-07 02:00:00 +0000 155145 9.23
2021-01-08 02:00:00 +0000 148889 9.11
2021-01-09 02:00:00 +0000 149466 9.13
2021-01-10 02:00:00 +0000 148209 9.03
You may find that your test definitions are very similar to each other, e.g. they all have the same metrics. Instead of copy-pasting the definitions you can use templating capability built-in otava to define the common bits of configs separately.
First, extract the common pieces to the templates section:
templates: common-metrics: throughput: suffix: client.throughput response-time: suffix: client.p50 direction: -1 # lower is better cpu-load: suffix: server.cpu direction: -1 # lower is better
Next you can recall a template in the inherit property of the test:
my-product.test-1: type: graphite tags: [perf-test, daily, my-product, test-1] prefix: performance-tests.daily.my-product.test-1 inherit: common-metrics my-product.test-2: type: graphite tags: [perf-test, daily, my-product, test-2] prefix: performance-tests.daily.my-product.test-2 inherit: common-metrics
You can inherit more than one template.
When developing a feature, you may want to analyze performance test results from a specific branch to detect any regressions introduced by your changes. The --branch option allows you to run change-point analysis on branch-specific data.
To support branch-based analysis, use the %{BRANCH} placeholder in your test configuration. This placeholder will be replaced with the branch name specified via --branch:
tests: my-product.test: type: graphite prefix: performance-tests.%{BRANCH}.my-product tags: [perf-test, my-product] metrics: throughput: suffix: client.throughput direction: 1 response_time: suffix: client.p50 direction: -1
For PostgreSQL or BigQuery tests, use %{BRANCH} in your SQL query:
tests: my-product.db-test: type: postgres time_column: commit_ts attributes: [experiment_id, commit] query: | SELECT commit, commit_ts, throughput, response_time FROM results WHERE branch = %{BRANCH} ORDER BY commit_ts ASC metrics: throughput: direction: 1 response_time: direction: -1
For CSV data sources, the branching is done by looking at the branch column in the CSV file and filtering rows based on the specified branch value.
Run the analysis with the --branch option:
otava analyze my-product.test --branch feature-xyz
This will:
$ otava analyze my-product.test --branch feature-new-cache --since=-30d
INFO: Computing change points for test my-product.test...
my-product.test:
time throughput response_time
------------------------- ------------ ---------------
2024-01-15 10:00:00 +0000 125000 45.2
2024-01-16 10:00:00 +0000 124500 44.8
2024-01-17 10:00:00 +0000 126200 45.1
········
+15.2%
········
2024-01-18 10:00:00 +0000 145000 38.5
2024-01-19 10:00:00 +0000 144200 39.1
2024-01-20 10:00:00 +0000 146100 38.2
The --branch option can also be set via the BRANCH environment variable:
BRANCH=feature-xyz otava analyze my-product.test